Venturing Into Use of Machine Learning And Time Series For Investment Growth/Management

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I have been reading some select books just to arm myself for the task of using machine learning and time series for analysing investment opportunities in general and specifically to carry out algorithmic trading.

As usual I will share the most tangible aspects of my learning and findings. But the key books I have been using are:

  1. Advanced Algorithmic Trading by Michael L. Halls-Moore
  2. Machine Learning with R by Brett Lantz
  3. Mastering Python for Finance by James Ma Weiming

The most important one is the Advanced Algorithmic Trading one. I bought it with the source code. Paid a hefty amount in Naira terms. I hope to use it to quickly get a good real life feel of making investment recommendations, portfolio balancing, risk management and automated trades though first with US financial markets before adapting for Nigerian markets.

Besides these books there are some 13 other books I use. I try to get a more context rich knowledge of the different data science methods by reading up lots of books. I find books more structured and in-depth in their presentation of knowledge. Then I use video courses to learn a few more tricks and solidify the theories I learned from the books.

At the pace I am going, I should be done with my targeted reading in three weeks and then fully concentrate on coding and practice,which are the aspects more interesting to share.

I am most motivated by the practical use of the knowledge I am gathering and the huge financially rewarding opportunities of using data science to make financial investment decisions in our little covered/analysed financial markets.

Even if you get easily bored by the technical side of it all, you can be sure you'll enjoy the practical application side I will present. I intend to put my hard earned money into the models and watch them fail or succeed.


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